Lidar sensor system including a dual-polarization transmit and receive optical antenna

ABSTRACT

A light detection and ranging (LIDAR) sensor system for a vehicle includes one or more LIDAR pixels. At least one of the one or more LIDAR pixels includes a dual-polarization optical antenna, a second optical antenna, and one or more receivers. The dual-polarization optical antenna is configured to emit a transmit beam having a first polarization orientation, and detect a return beam having a second polarization orientation. The second optical antenna is offset from the dual-polarization optical antenna by a particular distance, and is configured to detect the return beam having the second polarization orientation. The one or more receivers are configured to generate one or more signals in response to detecting the second polarization orientation of the return beam.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional applicationSer. No. 17/848,167 filed Jun. 23, 2022, which is hereby incorporated byreference in its entirety.

BACKGROUND INFORMATION

Frequency Modulated Continuous Wave (FMCW) light detection and ranging(LIDAR) directly measures range and velocity of an object bytransmitting a frequency modulated light beam and detecting a returnsignal. The automobile industry is currently developing autonomousfeatures for controlling vehicles under certain circumstances. Accordingto SAE International standard J3016, there are 6 levels of autonomyranging from Level 0 (no autonomy) up to Level 5 (vehicle capable ofoperation without operator input in all conditions). A vehicle withautonomous features utilizes sensors to sense the environment that thevehicle navigates through. Acquiring and processing data from thesensors allows the vehicle to navigate through its environment.

BRIEF SUMMARY OF THE INVENTION

Implementations of the disclosure include a light detection and ranging(LIDAR) sensor system including one or more LIDAR pixels. At least oneof the one or more LIDAR pixels may include a dual-polarization opticalantenna, a first receiver, and a second receiver. The dual-polarizationoptical antenna may be configured to (i) emit a transmit beam with afirst polarization orientation and (ii) detect a return beam having asecond polarization orientation. The first receiver may be configured togenerate a first signal in response to receiving the second polarizationorientation of the return beam and in response to a first localoscillator signal. The second receiver may be configured to generate asecond signal in response to receiving the second polarizationorientation of the return beam from the dual-polarization opticalantenna and in response to a second local oscillator signal.

In an implementation, the dual-polarization optical antenna includes atwo-dimensional (2D) polarization splitting grating coupler including afirst port and a second port. The 2D polarization splitting grating canbe configured to receive a transmit signal on the first port and can beconfigured to provide the return beam having the second polarization tothe second port coupled to the second receiver.

In an implementation, the LIDAR sensor system further includes asingle-polarization optical antenna configured to detect the return beamhaving the second polarization orientation. The single-polarizationoptical antenna can be coupled to the first receiver to provide thesecond polarization orientation of the return beam to the firstreceiver.

In an implementation, the single-polarization optical antenna is aone-dimensional (1D) polarization grating coupler.

In an implementation, the dual-polarization optical antenna is offsetfrom the single-polarization optical antenna by a particular distance.

In an implementation, the first polarization orientation is orthogonalto the second polarization orientation.

In an implementation, the LIDAR sensor system further includes asingle-polarization optical antenna configured to detect the return beamhaving the second polarization orientation.

In an implementation, the first local oscillator signal is polarizedwith a third polarization orientation, the second local oscillatorsignal is polarized with the third polarization orientation, and atransmit signal is polarized with the third polarization prior totransmission. The dual-polarization optical antenna may be configured tocouple the transmit signal into free-space as the transmit beam.

In an implementation, the dual-polarization optical antenna isconfigured to couple the return beam into the at least one of the one ormore LIDAR pixels as a return signal. The return signal may be polarizedwith the third polarization orientation.

In an implementation, the third polarization orientation is the firstpolarization orientation or the second polarization orientation.

In an implementation, the first receiver includes a first optical mixerand the second receiver includes a second optical mixer. The firstreceiver may include a first diode pair coupled to the first opticalmixer and may be configured to provide a first electrical signal. Thefirst electrical signal can be the first signal. The second receiver caninclude a second diode pair coupled to the second optical mixer and canbe configured to provide a second electrical signal. The secondelectrical signal can be the second signal.

In an implementation, the transmit beam and the return beam are anarrow-band near-infrared wavelength.

In an implementation, the return beam is the transmit beam reflected offof an object.

Implementations of the disclosure include an autonomous vehicle controlsystem for an autonomous vehicle. The autonomous vehicle control systemmay include a light detection and ranging (LIDAR) device and one or moreprocessors. The LIDAR device may include one or more LIDAR pixels. Atleast one of the one or more LIDAR pixels may include adual-polarization optical antenna, a first receiver, and a secondreceiver. The dual-polarization optical antenna may be configured to (i)emit a transmit beam with a first polarization orientation and (ii)detect a return beam having a second polarization orientation. The firstreceiver may be configured to generate a first electrical signal inresponse to receiving the second polarization orientation of the returnbeam and in response to a first local oscillator signal. The secondreceiver may be configured to generate a second electrical signal inresponse to receiving the second polarization orientation of the returnbeam from the dual-polarization optical antenna and in response to asecond local oscillator signal. The one or more processors may beconfigured to control the autonomous vehicle in response to the firstelectrical signal and the second electrical signal.

In an implementation, the dual-polarization optical antenna includes atwo-dimensional (2D) polarization splitting grating coupler having afirst port and a second port. The 2D polarization splitting grating maybe configured to receive a transmit signal on the first port and isconfigured to provide the return beam having the second polarization tothe second port coupled to the second receiver.

In an implementation, the at least one of the one or more LIDAR pixelsfurther includes a single-polarization optical antenna configured todetect the return beam having the second polarization orientation. Thesingle-polarization optical antenna can be coupled to the first receiverto provide the second polarization orientation of the return beam to thefirst receiver.

In an implementation, the single-polarization optical antenna is aone-dimensional (1D) polarization grating coupler.

In an implementation, the dual-polarization optical antenna is offsetfrom the single-polarization optical antenna by a particular distance.

In an implementation, the autonomous vehicle control system furtherincludes a rotating mirror and a birefringent slab. The rotating mirrormay be configured to direct the transmit beam into a LIDAR environmentand configured to direct the return beam onto the at least one of theone or more LIDAR pixels. The birefringent slab may be positionedbetween the rotating mirror and the at least one of the one or moreLIDAR pixels. The birefringent slab may be configured to direct thereturn beam having the second polarization orientation onto thesingle-polarization optical antenna or onto the dual-polarizationoptical antenna.

Implementations of the disclosure include an autonomous vehiclecomprising. The autonomous vehicle may include a light detection andranging (LIDAR) device and one or more processors. The LIDAR device mayinclude one or more LIDAR pixels. At least one of the one or more LIDARpixels may include a dual-polarization optical antenna, a firstreceiver, and a second receiver. The dual-polarization optical antennamay be configured to (i) emit a transmit beam with a first polarizationorientation and (ii) detect a return beam having a second polarizationorientation. The first receiver may be configured to generate a firstelectrical signal in response to receiving the second polarizationorientation of the return beam and in response to a first localoscillator signal. The second receiver may be configured to generate asecond electrical signal in response to receiving the secondpolarization orientation of the return beam from the dual-polarizationoptical antenna and in response to a second local oscillator signal. Theone or more processors may be configured to control the autonomousvehicle in response to the first signal and the second signal.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the invention aredescribed with reference to the following figures, wherein likereference numerals refer to like parts throughout the various viewsunless otherwise specified.

FIG. 1 illustrates a LIDAR system including a LIDAR pixel, in accordancewith implementations of the disclosure.

FIGS. 2A and 2B illustrate examples of coherent receivers, in accordancewith implementations of the disclosure.

FIG. 3 illustrates a LIDAR system including a LIDAR pixel, abirefringent slab, and a rotating mirror, in accordance withimplementations of the disclosure.

FIG. 4A illustrates a block diagram illustrating an example of a systemenvironment for autonomous vehicles, in accordance with implementationsof the disclosure.

FIG. 4B illustrates a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, in accordancewith implementations of the disclosure.

FIG. 4C illustrates a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, in accordancewith implementations of the disclosure.

FIG. 4D illustrates a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, in accordancewith implementations of the disclosure.

DETAILED DESCRIPTION

Implementations of a LIDAR pixel with dual polarization transmit/receiveoptical antenna is described herein. A LIDAR pixel can include one ormore modules, one or more integrated chips, or one or more electriccircuits. In addition, a LIDAR pixel can be implemented as a singlepackaged chip or implemented as modular design such that a LIDAR pixelincludes multiple packaged chips. In the following description, numerousspecific details are set forth to provide a thorough understanding ofthe implementations. One skilled in the relevant art will recognize,however, that the techniques described herein can be practiced withoutone or more of the specific details, or with other methods, components,materials, etc. In other instances, well-known structures, materials, oroperations are not shown or described in detail to avoid obscuringcertain aspects.

Reference throughout this specification to “one implementation” or “animplementation” means that a particular feature, structure, orcharacteristic described in connection with the implementation isincluded in at least one implementation of the present invention. Thus,the appearances of the phrases “in one implementation” or “in animplementation” in various places throughout this specification are notnecessarily all referring to the same implementation. Furthermore, theparticular features, structures, or characteristics may be combined inany suitable manner in one or more implementations.

Throughout this specification, several terms of art are used. Theseterms are to take on their ordinary meaning in the art from which theycome, unless specifically defined herein or the context of their usewould clearly suggest otherwise. For the purposes of this disclosure,the term “autonomous vehicle” includes vehicles with autonomous featuresat any level of autonomy of the SAE International standard J3016.

In aspects of this disclosure, visible light may be defined as having awavelength range of approximately 380 nm-700 nm. Non-visible light maybe defined as light having wavelengths that are outside the visiblelight range, such as ultraviolet light and infrared light. Infraredlight having a wavelength range of approximately 700 nm-1 mm includesnear-infrared light. In aspects of this disclosure, near-infrared lightmay be defined as having a wavelength range of approximately 700 nm-1600nm.

Frequency Modulated Continuous Wave (FMCW) LIDAR directly measures rangeand velocity of an object/target by directing a frequency modulatedlight beam to an object or target. The light that is reflected from theobject/target is combined with a tapped version of the light beam. Thefrequency of the resulting beat tone is proportional to the distance ofthe object from the LIDAR system once corrected for the doppler shiftthat requires a second measurement. The two measurements, which may ormay not be performed at the same time, provide both range and velocityinformation.

Implementations of the disclosure include a LIDAR device including LIDARpixels having an optical antenna, a receive optical antenna, a firstreceiver, and a second receiver. The optical antenna is a dualpolarization optical antenna that emits a transmit beam at a firstpolarization orientation and that detects a return beam having a secondpolarization orientation. The receive optical antenna may be coupled tothe first receiver to provide the return beam having the secondpolarization orientation. The dual-polarization optical antenna may becoupled to the second receiver to provide the return beam having thesecond polarization orientation. The first receiver generates a firstsignal in response to receiving the second polarization orientation ofthe return beam detected by the receive optical antenna, and the secondreceiver generates a second signal in response to receiving the secondpolarization orientation of the return beam detected by thedual-polarization optical antenna. Detecting the return beam at anoffset from the transmit antenna may increase the signal to noise ratio(SNR) of the detected return beam and therefore increase the imagingquality of a LIDAR system. Additionally, detecting two differentlocations of the return beam may allow the LIDAR system to detectadditional information about the external environment such as theobjects positioned in a greater variety of ranges in the externalenvironment of the LIDAR system. These and other implementations aredescribed in more detail in connection with FIGS. 1-4D.

FIG. 1 illustrates a LIDAR system 100 including a LIDAR pixel 102, inaccordance with implementations of the disclosure. LIDAR pixel 102includes an optical antenna 104, a receive optical antenna 106, a firstcoherent receiver 121, and a second coherent receiver 126, according toan implementation. However, the present invention is not limited to theparticular LIDAR pixel architecture shown in FIG. 1 . Any suitable chipdesign architecture can be used to implement a LIDAR pixel. For example,transmit and receive optical antennas can be implemented as a singlemodule or a single integrated chip or implemented as separate modules orchips. As another example, first and second coherent receivers can beimplemented as a single module or a single integrated chip orimplemented as separate modules or chips. Optical antenna 104 may beconfigured to emit a transmit beam with a first polarization orientationand may be configured to detect a return beam having a secondpolarization orientation. Receive optical antenna 106 may be positioneda distance D from optical antenna 104 to account for or compensate forbeam walk-off caused by a LIDAR system rotating mirror. The transmitbeam may be an infrared transmit beam. The transmit beam may be anear-infrared transmit beam. The transmit beam may be emitted as asingle defined polarization orientation. In FIG. 1 , optical antenna 104is illustrated as a dual-polarization optical coupler and may transmitthe transmit beam in response to receiving a transmit signal 108 by wayof a waveguide 109, according to an implementation. Transmit signal 108may be generated by a laser and the transmit beam emitted by opticalantenna 104 may have a very narrow linewidth (e.g., 1 nm or less).

In some implementations, optical antenna 104 may include adual-polarization transmit/receive optical antenna that may beconfigured to emit a transmit signal with a first polarizationorientation and that may be configured to (e.g., concurrently) detect areturn beam having a second polarization orientation. The return beammay be a reflection of the transmit beam reflecting off of an object inan external environment of the LIDAR system 100. The first polarizationorientation may be orthogonal to the second polarization orientation. Insome implementations, the orthogonality can have a margin rage above 0to 10%. For example, if the first polarization orientation has a degreewith reference to the second polarization orientation between 80 and 100degrees, it can be defined as orthogonal. Optical antenna 104 may beimplemented as a two-dimensional (2D) polarization splitting gratingcoupler having two ports. A first port of optical antenna 104 may becoupled to transmit signal 108 with waveguide 109 to enable opticalantenna 104 to emit a transmit beam with the first polarizationorientation. A second port of optical antenna 104 may be coupled tosecond coherent receiver 126 with a waveguide 110 to enable opticalantenna 104 to provide a second polarization orientation of the returnsignal to second coherent receiver 126. Optical antenna 104 may beconfigured to couple the return beam from free-space and into waveguide110 as a return signal that propagates through waveguide 110 to coherentreceiver 126. The return signal may have the same polarizationorientation was transmit signal TX and as local oscillator signal LO2while in LIDAR pixel 102 (e.g., while on-chip). The polarizationorientation of the return signal(s), transmit signal TX, localoscillator signal LO1, and local oscillator signal LO2 may be the sameas the first polarization orientation, or the second polarizationorientation, or may be an entirely different polarization orientation,according to an implementation. The first polarization orientation maybe positive 45 degrees, and the second polarization orientation may benegative 45 degrees (e.g., of linear TE or TM polarization), accordingto an implementation.

Receive optical antenna 106 may be implemented as a single-polarizationgrating coupler. Receive optical antenna 106 may be rotated to receiveand detect (e.g., couple into a waveguide) the second polarizationorientation of the return beam. Receive optical antenna 106 may berotated to light that is polarized by negative 45 degrees. Receiveoptical antenna 106 may be offset from the location of optical antenna104 by a distance D to enable receive optical antenna 106 to compensatefor beam walk-off as, for example, illustrated in FIG. 3 . Receiveoptical antenna 106 may be coupled to first coherent receiver 121 with awaveguide 112 to provide the second polarization orientation of thereturn beam to first coherent receiver 121.

In some implementations, first coherent receiver 121 may be configuredto generate a first signal 123 in response to receiving the secondpolarization orientation of the return beam and a first local oscillatorsignal (LO1) 131. The first local oscillator signal 131 may be anoptical signal having the second polarization orientation. In FIG. 1 ,the second polarization orientation of the return beam is received byfirst coherent receiver 121 from receive optical antenna 106 by way ofwaveguide 112, and the first local oscillator signal 131 is received byfirst coherent receiver 121 by way of waveguide 132, according to animplementation. First signal 123 may be an electrical signal provided toprocessing logic 150 by way of communication channel 122.

In some implementations, second coherent receiver 126 may be configuredto generate a second signal 128 in response to receiving the secondpolarization orientation of the return beam and a second localoscillator signal (LO2) 136. The second local oscillator signal 136 maybe an optical signal having the second polarization orientation. In FIG.1 , the second polarization orientation of the return beam is receivedby second coherent receiver 126 from optical antenna 104 by way ofwaveguide 110 and the second local oscillator signal 136 is received bysecond coherent receiver 126 by way of waveguide 137, according to animplementation. Second signal 128 may be an electrical signal providedto processing logic 150 by way of communication channel 127.

In some implementations, processing logic 150 may be configured togenerate an image 155 in response to receiving first signal 123 andsecond signal 128 from first coherent receiver 121 and second coherentreceiver 126, respectively. LIDAR system 100 may include an array ofLIDAR pixels 102 that are configured to provide first signals (e.g.,signal 123) and second signals (e.g., signal 128) to processing logic150. In this context, processing logic 150 may generate image 155 inresponse to the first signals and second signals received by processinglogic 150 by the plurality of LIDAR pixels 102 in the array of LIDARpixels.

In an example of operation, transmit signal 108 may be emitted into freespace as the transmit beam by optical antenna 104. The transmit beam maypropagate through one or more lenses and be deflected by a rotatingmirror, and then propagate through the external environment untilencountering an object. A portion of the transmit beam that encountersthe object may be reflected back toward LIDAR system 100 and LIDAR pixel102 as the return beam. The return beam may reflect off the rotatingmirror and propagate through the one or more lenses but be offsetrelative to optical antenna 104 due to the time difference in therotation of the mirror. To compensate for this offset, receive opticalantenna 106 may be offset by distance D from optical antenna 104.

FIGS. 2A and 2B illustrate examples of coherent receivers 121 and 126(shown in FIG. 1 ), according to implementations of the disclosure.

FIG. 2A illustrates a coherent receiver 200. Coherent receiver 200 mayinclude an optical mixer 202, a return beam port 204, a local oscillatorport 208 and an output port 212. Optical mixer 202 is configured tocombine a return beam signal RB with a local oscillator signal LO togenerate an output signal OUT, according to an implementation. Opticalmixer 202 may be configured to receive two or more optical signals.Optical mixer 202 may be coupled to receive return beam signal RB fromreturn beam port 204 through a waveguide 206. Optical mixer 202 may becoupled to receive local oscillator signal LO from local oscillator port208 through a waveguide 210, according to an implementation. Opticalmixer 202 may combine input signals to generate a number of combinedoutput signals OUT1 and OUT2. The number of output signals from anoptical mixer can be any suitable number, not limited to a particularnumber. Output signals OUT1 and OUT2 are provided to a photodiode pair(including photodiodes PD1 and PD2) to convert return beam signal RB andlocal oscillator signal LO into output signal OUT, according to animplementation. Output signal OUT may be an electrical signal. Outputsignal OUT may be a beat signal that represents a range and/or velocityof one or more objects in the environment of a LIDAR system. Each ofthese output signal OUT variations may provide object characteristics(e.g., distance, reflectivity) about the object in the environment fromwhich the return beam was reflected. Object characteristics (e.g.,distance, reflectivity) may enable autonomous vehicles (e.g., trucks) toperform vehicle operations (e.g., stop, swerve, ignore) based on thecharacteristics of the object(s), for example. Each output signal may beprovided to respective ones of a number of receivers to enableconcurrent reception and processing of a number of output signals.

FIG. 2B illustrates an example of a coherent receiver 230 having anoptical mixer 232 that is configured to provide multiple output signalsOUT3, OUT4, OUT5, and OUT6, based on return beam signal RB and localoscillator signal LO, according to an implementation. However, thenumber of output signals from an optical mixer can be any suitablenumber, not limited to a particular number. Optical mixer 232 providessignals OUT3, OUT4, OUT5, and OUT6 to a photodiode configuration thatconverts the mixed signals into an in-phase output signal OUT_I and aquadrature output signal OUT_Q, according to an implementation. In-phaseoutput signal OUT_I may be provided to output port 234, and quadratureoutput signal OUT_Q may be provided to output port 236. The photodiodeconfiguration may include photodiodes PD3, PD4, PD5, and PD6.

FIG. 3 illustrates an example of a LIDAR system 300 that shows how LIDARpixel 102 can be used to compensate for beam walk-off and support beamscanning, in accordance with implementations of the disclosure.

In an example of operation, optical antenna 104 may emit light as atransmit beam 302 having a first polarization orientation (e.g.,linearly polarized at 45 degrees). Transmit beam 302 may propagatethrough a birefringent slab 304, which introduces a small offset 306 inthe position of transmit beam 302 relative to optical antenna 104.Transmit beam 302 may be collimated by a lens 308 and directed to amirror 310. Lens 308 may be disposed between birefringent slab 304 andmirror 310. Mirror 310 may be selectively rotated or may be configuredto continuously rotate to scan the LIDAR environment. Transmit beam 302can be reflected off of mirror 310 and directed into the LIDARenvironment as a free space light beam. Transmit beam 302 can propagateto an object 312 and may be reflected back as a return beam 314. Object312 may be a reflective surface, a diffuse surface, or a partiallyreflective and partially diffuse surface. Object 312 may change thepolarization orientation/characteristics of return beam 314 to apolarization orientation that is different than transmit beam 302. Forexample, the polarization of return beam 314 may be randomized. Returnbeam 314 may include components of several polarization orientations(e.g., circular, elliptical, linear). Return beam 314 may include alight component that has a second polarization orientation (e.g.,linearly polarized by −45°) that is, for example, orthogonal to thefirst polarization orientation (e.g., linearly polarized by +45°) oftransmit beam 302, as an example. Upon reflection, return beam 314propagates back to mirror 310.

During the transit time of transmit beam 302 and return beam 314 toobject 312 and back to mirror 310, mirror 310 may have rotated by asmall amount. The amount of rotation will vary based on the distancetraveled by transmit beam 302 and return beam 314. Because of therotation of mirror 310, return beam 314 may be incident on lens 308 at adifferent angle than transmit beam 302. The changing locations of returnbeam 314 on mirror 310 could cause return beam 314 to walk-off or missoptical antenna 104. However, LIDAR pixel 102 includes receive opticalantenna 106, so LIDAR pixel 102 may receive return beam 314 of thesecond polarization orientation if return beam 314 returns at an offsetaway from optical antenna 104 and becomes incident upon receive opticalantenna 106.

Upon return to LIDAR pixel 102, birefringent slab 304 may direct returnbeam 314 towards different locations of LIDAR pixel 102 based on thepolarization characteristics of return beam 314, according to animplementation. Return beam 314 may be directed to pass through thebirefringent slab 304, which shifts return beam 314 in spacehorizontally. If the polarization of return beam 314 is different thanthe polarization of transmit beam 302, the shift introduced by thebirefringent material may be different. Birefringent slab 304 may beconfigured to direct return beam 314 to locations on LIDAR pixel 102based on the polarization orientation or characteristics of return beam314, according to an implementation. Birefringent slab 304 may beconfigured to direct return beam 314 along a different optical path thantransmit beam 302, based on the polarization of the two signals, toreduce signal interference, according to an implementation.

In some implementations, by selecting a particular birefringent materialand controlling a thickness 322 of birefringent slab 304 and an angle324 of birefringent slab 304, the relative shifts of the transmitted andreturned beams can be controlled. In the illustration of FIG. 3 , thebirefringent material is angled with respect to transmit beam 302incident on birefringent slab 304 and birefringent slab 304 is tiltedwith respect to return beam 314 incident on the birefringent material.In an implementation, tilt angle 324 of birefringent slab 304 andthickness 322 of birefringent slab 304 are configured for detection ofobjects at a detection distance of 50 meters or greater.

In some implementations, birefringent slab 304 may include LiNO₃(Lithium Nitrate). In some implementations, birefringent slab 304 mayinclude YVO₄ (Yttrium Orthovanadate). However, materials for abirefringent slap are not limited to the materials described above. Anysuitable material can be used for a birefringent slab in order tooptimally correct for the walk-off introduced by rotating mirrors for awide range of object distances. For example, optimizing for a longerrange target may include selecting a birefringent material having alarger horizontal shift due to the longer round trip time for the beamto reflect off the target and propagate back to receive optical antennas104, 106.

The tilted piece of birefringent slab 304 may be a part of the lensassembly or a chip package assembly. It may be integrated on the samephotonic chip as an array of the coherent pixels. A plurality ofcoherent pixels and tilted birefringent pieces can be used together torealize more complex operations of an FMCW LIDAR. The birefringent piecemay be motorized to change tilt angle 324, in some implementations. Insome implementations, of LIDAR system 300, birefringent slab 304 isomitted between LIDAR pixel 102 and lens 308. In some implementations,one or more optical elements are positioned between mirror 310 and LIDARpixel 102 to manipulate the polarization characteristics of transmitbeam 302 and return beam 314. For example, one or more half-wave platesor quarter-wave plates may be included to change polarizations fromlinear to circular (or vice-versa) and to shift orientations byorthogonal amounts.

1. System Environment for Autonomous Vehicles

FIG. 4A is a block diagram illustrating an example of a systemenvironment for autonomous vehicles according to some implementations.

Referring to FIG. 4A, an example autonomous vehicle 410A within whichthe various techniques disclosed herein may be implemented. The vehicle410A, for example, may include a powertrain 492 including a prime mover494 powered by an energy source 496 and capable of providing power to adrivetrain 498, as well as a control system 480 including a directioncontrol 482, a powertrain control 484, and a brake control 486. Thevehicle 410A may be implemented as any number of different types ofvehicles, including vehicles capable of transporting people and/orcargo, and capable of traveling in various environments, and it will beappreciated that the aforementioned components 480-498 can vary widelybased upon the type of vehicle within which these components areutilized.

For simplicity, the implementations discussed hereinafter will focus ona wheeled land vehicle such as a car, van, truck, bus, etc. In suchimplementations, the prime mover 494 may include one or more electricmotors and/or an internal combustion engine (among others). The energysource may include, for example, a fuel system (e.g., providinggasoline, diesel, hydrogen, etc.), a battery system, solar panels orother renewable energy source, and/or a fuel cell system. The drivetrain498 can include wheels and/or tires along with a transmission and/or anyother mechanical drive components to convert the output of the primemover 494 into vehicular motion, as well as one or more brakesconfigured to controllably stop or slow the vehicle 410A and directionor steering components suitable for controlling the trajectory of thevehicle 410A (e.g., a rack and pinion steering linkage enabling one ormore wheels of the vehicle 410A to pivot about a generally vertical axisto vary an angle of the rotational planes of the wheels relative to thelongitudinal axis of the vehicle). In some implementations, combinationsof powertrains and energy sources may be used (e.g., in the case ofelectric/gas hybrid vehicles), and in some instances multiple electricmotors (e.g., dedicated to individual wheels or axles) may be used as aprime mover.

The direction control 482 may include one or more actuators and/orsensors for controlling and receiving feedback from the direction orsteering components to enable the vehicle 410A to follow a desiredtrajectory. The powertrain control 484 may be configured to control theoutput of the powertrain 492, e.g., to control the output power of theprime mover 494, to control a gear of a transmission in the drivetrain498, etc., thereby controlling a speed and/or direction of the vehicle410A. The brake control 486 may be configured to control one or morebrakes that slow or stop vehicle 410A, e.g., disk or drum brakes coupledto the wheels of the vehicle.

Other vehicle types, including but not limited to off-road vehicles,all-terrain or tracked vehicles, construction equipment etc., willnecessarily utilize different powertrains, drivetrains, energy sources,direction controls, powertrain controls and brake controls. Moreover, insome implementations, some of the components can be combined, e.g.,where directional control of a vehicle is primarily handled by varyingan output of one or more prime movers. Therefore, implementationsdisclosed herein are not limited to the particular application of theherein-described techniques in an autonomous wheeled land vehicle.

Various levels of autonomous control over the vehicle 410A can beimplemented in a vehicle control system 420, which may include one ormore processors 422 and one or more memories 424, with each processor422 configured to execute program code instructions 426 stored in amemory 424. The processors(s) can include, for example, graphicsprocessing unit(s) (“GPU(s)”)) and/or central processing unit(s)(“CPU(s)”).

Sensors 430 may include various sensors suitable for collectinginformation from a vehicle's surrounding environment for use incontrolling the operation of the vehicle. For example, sensors 430 caninclude radar sensor 434, LIDAR (Light Detection and Ranging) sensor436, a 3D positioning sensors 438, e.g., any of an accelerometer, agyroscope, a magnetometer, or a satellite navigation system such as GPS(Global Positioning System), GLONASS (Globalnaya NavigazionnayaSputnikovaya Sistema, or Global Navigation Satellite System), BeiDouNavigation Satellite System (BDS), Galileo, Compass, etc. The 3Dpositioning sensors 438 can be used to determine the location of thevehicle on the Earth using satellite signals. The sensors 430 caninclude a camera 440 and/or an IMU (inertial measurement unit) 442. Thecamera 440 can be a monographic or stereographic camera and can recordstill and/or video images. The IMU 442 can include multiple gyroscopesand accelerometers capable of detecting linear and rotational motion ofthe vehicle in three directions. One or more encoders (not illustrated),such as wheel encoders may be used to monitor the rotation of one ormore wheels of vehicle 410A. Each sensor 430 can output sensor data atvarious data rates, which may be different than the data rates of othersensors 430.

The outputs of sensors 430 may be provided to a set of controlsubsystems 450, including, a localization subsystem 452, a planningsubsystem 456, a perception subsystem 454, and a control subsystem 458.The localization subsystem 452 can perform functions such as preciselydetermining the location and orientation (also sometimes referred to as“pose”) of the vehicle 410A within its surrounding environment, andgenerally within some frame of reference. The location of an autonomousvehicle can be compared with the location of an additional vehicle inthe same environment as part of generating labeled autonomous vehicledata. The perception subsystem 454 can perform functions such asdetecting, tracking, determining, and/or identifying objects within theenvironment surrounding vehicle 410A. A machine learning model can beutilized in tracking objects. The planning subsystem 456 can performfunctions such as planning a trajectory for vehicle 410A over sometimeframe given a desired destination as well as the static and movingobjects within the environment. A machine learning can be utilized inplanning a vehicle trajectory. The control subsystem 458 can performfunctions such as generating suitable control signals for controllingthe various controls in the vehicle control system 420 in order toimplement the planned trajectory of the vehicle 410A. A machine learningmodel can be utilized to generate one or more signals to control anautonomous vehicle to implement the planned trajectory.

It will be appreciated that the collection of components illustrated inFIG. 4A for the vehicle control system 420 is merely exemplary innature. Individual sensors may be omitted in some implementations.Additionally or alternatively, in some implementations, multiple sensorsof types illustrated in FIG. 4A may be used for redundancy and/or tocover different regions around a vehicle, and other types of sensors maybe used. Likewise, different types and/or combinations of controlsubsystems may be used in other implementations. Further, whilesubsystems 452-458 are illustrated as being separate from processor 422and memory 424, it will be appreciated that in some implementations,some or all of the functionality of a subsystem 452-458 may beimplemented with program code instructions 426 resident in one or morememories 424 and executed by one or more processors 422, and that thesesubsystems 452-458 may in some instances be implemented using the sameprocessor(s) and/or memory. Subsystems may be implemented at least inpart using various dedicated circuit logic, various processors, variousfield programmable gate arrays (“FPGA”), various application-specificintegrated circuits (“ASIC”), various real time controllers, and thelike, as noted above, multiple subsystems may utilize circuitry,processors, sensors, and/or other components. Further, the variouscomponents in the vehicle control system 420 may be networked in variousmanners.

In some implementations, the vehicle 410A may also include a secondaryvehicle control system (not illustrated), which may be used as aredundant or backup control system for the vehicle 410A. The secondaryvehicle control system may be capable of fully operating the autonomousvehicle 410A in the event of an adverse event in the vehicle controlsystem 420, while in other implementations, the secondary vehiclecontrol system may only have limited functionality, e.g., to perform acontrolled stop of the vehicle 410A in response to an adverse eventdetected in the primary vehicle control system 420. In still otherimplementations, the secondary vehicle control system may be omitted.

In general, an innumerable number of different architectures, includingvarious combinations of software, hardware, circuit logic, sensors,networks, etc. may be used to implement the various componentsillustrated in FIG. 4A. Each processor may be implemented, for example,as a microprocessor and each memory may represent the random accessmemory (“RAM”) devices comprising a main storage, as well as anysupplemental levels of memory, e.g., cache memories, non-volatile orbackup memories (e.g., programmable or flash memories), read-onlymemories, etc. In addition, each memory may be considered to includememory storage physically located elsewhere in the vehicle 410A, e.g.,any cache memory in a processor, as well as any storage capacity used asa virtual memory, e.g., as stored on a mass storage device or anothercomputer controller. One or more processors illustrated in FIG. 4A, orentirely separate processors, may be used to implement additionalfunctionality in the vehicle 410A outside of the purposes of autonomouscontrol, e.g., to control entertainment systems, to operate doors,lights, convenience features, etc.

In addition, for additional storage, the vehicle 410A may include one ormore mass storage devices, e.g., a removable disk drive, a hard diskdrive, a direct access storage device (“DASD”), an optical drive (e.g.,a CD drive, a DVD drive, etc.), a solid state storage drive (“SSD”),network attached storage, a storage area network, and/or a tape drive,among others.

Furthermore, the vehicle 410A may include a user interface 464 to enablevehicle 410A to receive a number of inputs from and generate outputs fora user or operator, e.g., one or more displays, touchscreens, voiceand/or gesture interfaces, buttons and other tactile controls, etc.Otherwise, user input may be received via another computer or electronicdevice, e.g., via an app on a mobile device or via a web interface.

Moreover, the vehicle 410A may include one or more network interfaces,e.g., network interface 462, suitable for communicating with one or morenetworks 470 (e.g., a Local Area Network (“LAN”), a wide area network(“WAN”), a wireless network, and/or the Internet, among others) topermit the communication of information with other computers andelectronic device, including, for example, a central service, such as acloud service, from which the vehicle 410A receives environmental andother data for use in autonomous control thereof. Data collected by theone or more sensors 430 can be uploaded to a computing system 472 viathe network 470 for additional processing. A time stamp can be added toeach instance of vehicle data prior to uploading.

Each processor illustrated in FIG. 4A, as well as various additionalcontrollers and subsystems disclosed herein, generally operates underthe control of an operating system and executes or otherwise relies uponvarious computer software applications, components, programs, objects,modules, data structures, etc., as will be described in greater detailbelow. Moreover, various applications, components, programs, objects,modules, etc. may also execute on one or more processors in anothercomputer coupled to vehicle 410A via network 470, e.g., in adistributed, cloud-based, or client-server computing environment,whereby the processing required to implement the functions of a computerprogram may be allocated to multiple computers and/or services over anetwork.

In general, the routines executed to implement the variousimplementations described herein, whether implemented as part of anoperating system or a specific application, component, program, object,module or sequence of instructions, or even a subset thereof, will bereferred to herein as “program code”. Program code can include one ormore instructions that are resident at various times in various memoryand storage devices, and that, when read and executed by one or moreprocessors, perform the steps necessary to execute steps or elementsembodying the various aspects of the present disclosure. Moreover, whileimplementations have and hereinafter will be described in the context offully functioning computers and systems, it will be appreciated that thevarious implementations described herein are capable of beingdistributed as a program product in a variety of forms, and thatimplementations can be implemented regardless of the particular type ofcomputer readable media used to actually carry out the distribution.

Examples of computer readable media include tangible, non-transitorymedia such as volatile and non-volatile memory devices, floppy and otherremovable disks, solid state drives, hard disk drives, magnetic tape,and optical disks (e.g., CD-ROMs, DVDs, etc.) among others.

In addition, various program code described hereinafter may beidentified based upon the application within which it is implemented ina specific implementation. However, it should be appreciated that anyparticular program nomenclature that follows is used merely forconvenience, and thus the present disclosure should not be limited touse solely in any specific application identified and/or implied by suchnomenclature. Furthermore, given the typically endless number of mannersin which computer programs may be organized into routines, procedures,methods, modules, objects, and the like, as well as the various mannersin which program functionality may be allocated among various softwarelayers that are resident within a typical computer (e.g., operatingsystems, libraries, API's, applications, applets, etc.), it should beappreciated that the present disclosure is not limited to the specificorganization and allocation of program functionality described herein.

The environment illustrated in FIG. 4A is not intended to limitimplementations disclosed herein. Indeed, other alternative hardwareand/or software environments may be used without departing from thescope of implementations disclosed herein.

2. FM LIDAR for Automotive Applications

A truck can include a LIDAR system (e.g., vehicle control system 420and/or LIDAR system 100 and/or 300, etc.). In some implementations, theLIDAR system can use frequency modulation to encode an optical signaland scatter the encoded optical signal into free-space using optics. Bydetecting the frequency differences between the encoded optical signaland a returned signal reflected back from an object, the frequencymodulated (FM) LIDAR system can determine the location of the objectand/or precisely measure the velocity of the object using the Dopplereffect. An FM LIDAR system may use a continuous wave (referred to as,“FMCW LIDAR” or “coherent FMCW LIDAR”) or a quasi-continuous wave(referred to as, “FMQW LIDAR”). The LIDAR system can use phasemodulation (PM) to encode an optical signal and scatters the encodedoptical signal into free-space using optics.

An FM or phase-modulated (PM) LIDAR system may provide substantialadvantages over conventional LIDAR systems with respect to automotiveand/or commercial trucking applications. To begin, in some instances, anobject (e.g., a pedestrian wearing dark clothing) may have a lowreflectivity, in that it only reflects back to the sensors (e.g.,sensors 430 in FIG. 4A) of the FM or PM LIDAR system a low amount (e.g.,10% or less) of the light that hit the object. In other instances, anobject (e.g., a shiny road sign) may have a high reflectivity (e.g.,above 10%), in that it reflects back to the sensors of the FM LIDARsystem a high amount of the light that hit the object.

Regardless of the object's reflectivity, an FM LIDAR system may be ableto detect (e.g., classify, recognize, discover, etc.) the object atgreater distances (e.g., 2×) than a conventional LIDAR system. Forexample, an FM LIDAR system may detect a low reflectivity object beyond300 meters, and a high reflectivity object beyond 400 meters.

To achieve such improvements in detection capability, the FM LIDARsystem may use sensors (e.g., sensors 430 in FIG. 4A). In someimplementations, these sensors can be single photon sensitive, meaningthat they can detect the smallest amount of light possible. While an FMLIDAR system may, in some applications, use infrared wavelengths (e.g.,950 nm, 1550 nm, etc.), it is not limited to the infrared wavelengthrange (e.g., near infrared: 800 nm-1500 nm; middle infrared: 1500nm-5600 nm; and far infrared: 5600 nm-1,000,000 nm). By operating the FMor PM LIDAR system in infrared wavelengths, the FM or PM LIDAR systemcan broadcast stronger light pulses or light beams while meeting eyesafety standards. Conventional LIDAR systems are often not single photonsensitive and/or only operate in near infrared wavelengths, requiringthem to limit their light output (and distance detection capability) foreye safety reasons.

Thus, by detecting an object at greater distances, an FM LIDAR systemmay have more time to react to unexpected obstacles. Indeed, even a fewmilliseconds of extra time could improve safety and comfort, especiallywith heavy vehicles (e.g., commercial trucking vehicles) that aredriving at highway speeds.

Another advantage of an FM LIDAR system is that it provides accuratevelocity for each data point instantaneously. In some implementations, avelocity measurement is accomplished using the Doppler effect whichshifts frequency of the light received from the object based at leastone of the velocity in the radial direction (e.g., the direction vectorbetween the object detected and the sensor) or the frequency of thelaser signal. For example, for velocities encountered in on-roadsituations where the velocity is less than 100 meters per second (m/s),this shift at a wavelength of 1550 nanometers (nm) amounts to thefrequency shift that is less than 130 megahertz (MHz). This frequencyshift is small such that it is difficult to detect directly in theoptical domain. However, by using coherent detection in FMCW, PMCW, orFMQW LIDAR systems, the signal can be converted to the RF domain suchthat the frequency shift can be calculated using various signalprocessing techniques. This enables the autonomous vehicle controlsystem to process incoming data faster.

Instantaneous velocity calculation also makes it easier for the FM LIDARsystem to determine distant or sparse data points as objects and/ortrack how those objects are moving over time. For example, an FM LIDARsensor (e.g., sensors 430 in FIG. 4A) may only receive a few returns(e.g., hits) on an object that is 300 m away, but if those return give avelocity value of interest (e.g., moving towards the vehicle at >70mph), then the FM LIDAR system and/or the autonomous vehicle controlsystem may determine respective weights to probabilities associated withthe objects.

Faster identification and/or tracking of the FM LIDAR system gives anautonomous vehicle control system more time to maneuver a vehicle. Abetter understanding of how fast objects are moving also allows theautonomous vehicle control system to plan a better reaction.

Another advantage of an FM LIDAR system is that it has less staticcompared to conventional LIDAR systems. That is, the conventional LIDARsystems that are designed to be more light-sensitive typically performpoorly in bright sunlight. These systems also tend to suffer fromcrosstalk (e.g., when sensors get confused by each other's light pulsesor light beams) and from self-interference (e.g., when a sensor getsconfused by its own previous light pulse or light beam). To overcomethese disadvantages, vehicles using the conventional LIDAR systems oftenneed extra hardware, complex software, and/or more computational powerto manage this “noise.”

In contrast, FM LIDAR systems do not suffer from these types of issuesbecause each sensor is specially designed to respond only to its ownlight characteristics (e.g., light beams, light waves, light pulses). Ifthe returning light does not match the timing, frequency, and/orwavelength of what was originally transmitted, then the FM sensor canfilter (e.g., remove, ignore, etc.) out that data point. As such, FMLIDAR systems produce (e.g., generates, derives, etc.) more accuratedata with less hardware or software requirements, enabling safer andsmoother driving.

Lastly, an FM LIDAR system is easier to scale than conventional LIDARsystems. As more self-driving vehicles (e.g., cars, commercial trucks,etc.) show up on the road, those powered by an FM LIDAR system likelywill not have to contend with interference issues from sensor crosstalk.Furthermore, an FM LIDAR system uses less optical peak power thanconventional LIDAR sensors. As such, some or all of the opticalcomponents for an FM LIDAR can be produced on a single chip, whichproduces its own benefits, as discussed herein.

3. Commercial Trucking

FIG. 4B is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 400B includes a commercial truck402B for hauling cargo 406B. In some implementations, the commercialtruck 402B may include vehicles configured to long-haul freighttransport, regional freight transport, intermodal freight transport(i.e., in which a road-based vehicle is used as one of multiple modes oftransportation to move freight), and/or any other road-based freighttransport applications. The commercial truck 402B may be a flatbedtruck, a refrigerated truck (e.g., a reefer truck), a vented van (e.g.,dry van), a moving truck, etc. The cargo 406B may be goods and/orproduce. The commercial truck 402B may include a trailer to carry thecargo 406B, such as a flatbed trailer, a lowboy trailer, a step decktrailer, an extendable flatbed trailer, a sidekit trailer, etc.

The environment 400B includes an object 410B (shown in FIG. 4B asanother vehicle) that is within a distance range that is equal to orless than 30 meters from the truck.

The commercial truck 402B may include a LIDAR system 404B (e.g., an FMLIDAR system, vehicle control system 420 in FIG. 4A, LIDAR system 100 inFIG. 1 , LIDAR system 300 in FIG. 3 , etc.) for determining a distanceto the object 410B and/or measuring the velocity of the object 410B.Although FIG. 4B shows that one LIDAR system 404B is mounted on thefront of the commercial truck 402B, the number of LIDAR system and themounting area of the LIDAR system on the commercial truck are notlimited to a particular number or a particular area. The commercialtruck 402B may include any number of LIDAR systems 404B (or componentsthereof, such as sensors, modulators, coherent signal generators, etc.)that are mounted onto any area (e.g., front, back, side, top, bottom,underneath, and/or bottom) of the commercial truck 402B to facilitatethe detection of an object in any free-space relative to the commercialtruck 402B.

As shown, the LIDAR system 404B in environment 400B may be configured todetect an object (e.g., another vehicle, a bicycle, a tree, streetsigns, potholes, etc.) at short distances (e.g., 30 meters or less) fromthe commercial truck 402B.

FIG. 4C is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 400C includes the same components(e.g., commercial truck 402B, cargo 406B, LIDAR system 404B, etc.) thatare included in environment 400B.

The environment 400C includes an object 410C (shown in FIG. 4C asanother vehicle) that is within a distance range that is (i) more than30 meters and (ii) equal to or less than 150 meters from the commercialtruck 402B. As shown, the LIDAR system 404B in environment 400C may beconfigured to detect an object (e.g., another vehicle, a bicycle, atree, street signs, potholes, etc.) at a distance (e.g., 100 meters)from the commercial truck 402B

FIG. 4D is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 400D includes the same components(e.g., commercial truck 402B, cargo 406B, LIDAR system 404B, etc.) thatare included in environment 400B.

The environment 400D includes an object 410D (shown in FIG. 4D asanother vehicle) that is within a distance range that is more than 150meters from the commercial truck 402B. As shown, the LIDAR system 404Bin environment 400D may be configured to detect an object (e.g., anothervehicle, a bicycle, a tree, street signs, potholes, etc.) at a distance(e.g., 300 meters) from the commercial truck 402B.

In commercial trucking applications, it is important to effectivelydetect objects at all ranges due to the increased weight and,accordingly, longer stopping distance required for such vehicles. FMLIDAR systems (e.g., FMCW and/or FMQW systems) or PM LIDAR systems arewell-suited for commercial trucking applications due to the advantagesdescribed above. As a result, commercial trucks equipped with suchsystems may have an enhanced ability to safely move both people andgoods across short or long distances, improving the safety of not onlythe commercial truck but of the surrounding vehicles as well. In variousimplementations, such FM or PM LIDAR systems can be used insemi-autonomous applications, in which the commercial truck has a driverand some functions of the commercial truck are autonomously operatedusing the FM or PM LIDAR system, or fully autonomous applications, inwhich the commercial truck is operated entirely by the FM or LIDARsystem, alone or in combination with other vehicle systems.

4. Continuous Wave Modulation and Quasi-Continuous Wave Modulation

In a LIDAR system that uses CW modulation, the modulator modulates thelaser light continuously. For example, if a modulation cycle is 10seconds, an input signal is modulated throughout the whole 10 seconds.Instead, in a LIDAR system that uses quasi-CW modulation, the modulatormodulates the laser light to have both an active portion and an inactiveportion. For example, for a 10 second cycle, the modulator modulates thelaser light only for 8 seconds (sometimes referred to as, “the activeportion”), but does not modulate the laser light for 2 seconds(sometimes referred to as, “the inactive portion”). By doing this, theLIDAR system may be able to reduce power consumption for the 2 secondsbecause the modulator does not have to provide a continuous signal.

In Frequency Modulated Continuous Wave (FMCW) LIDAR for automotiveapplications, it may be beneficial to operate the LIDAR system usingquasi-CW modulation where FMCW measurement and signal processingmethodologies are used, but the light signal is not in the on-state(e.g., enabled, powered, transmitting, etc.) all the time. In someimplementations, Quasi-CW modulation can have a duty cycle that is equalto or greater than 1% and up to 50%. If the energy in the off-state(e.g., disabled, powered-down, etc.) can be expended during the actualmeasurement time then there may be a boost to signal-to-noise ratio(SNR) and/or a reduction in signal processing requirements to coherentlyintegrate all the energy in the longer time scale.

The term “processing logic” in this disclosure may include one or moreprocessors, microprocessors, multi-core processors, Application-specificintegrated circuits (ASIC), and/or Field Programmable Gate Arrays(FPGAs) to execute operations disclosed herein. In some implementations,memories (not illustrated) are integrated into the processing logic tostore instructions to execute operations and/or store data. Processinglogic may also include analog or digital circuitry to perform theoperations in accordance with implementations of the disclosure.

A “memory” or “memories” described in this disclosure may include one ormore volatile or non-volatile memory architectures. The “memory” or“memories” may be removable and non-removable media implemented in anymethod or technology for storage of information such ascomputer-readable instructions, data structures, program modules, orother data. Example memory technologies may include RAM, ROM, EEPROM,flash memory, CD-ROM, digital versatile disks (DVD), high-definitionmultimedia/data storage disks, or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other non-transmission medium that can be usedto store information for access by a computing device.

Networks may include any network or network system such as, but notlimited to, the following: a peer-to-peer network; a Local Area Network(LAN); a Wide Area Network (WAN); a public network, such as theInternet; a private network; a cellular network; a wireless network; awired network; a wireless and wired combination network; and a satellitenetwork.

Communication channels may include or be routed through one or morewired or wireless communication utilizing IEEE 802.11 protocols,BlueTooth, SPI (Serial Peripheral Interface), I2C (Inter-IntegratedCircuit), USB (Universal Serial Port), CAN (Controller Area Network),cellular data protocols (e.g. 3G, 4G, LTE, 5G), optical communicationnetworks, Internet Service Providers (ISPs), a peer-to-peer network, aLocal Area Network (LAN), a Wide Area Network (WAN), a public network(e.g. “the Internet”), a private network, a satellite network, orotherwise.

A computing device may include a desktop computer, a laptop computer, atablet, a phablet, a smartphone, a feature phone, a server computer, orotherwise. A server computer may be located remotely in a data center orbe stored locally.

The processes explained above are described in terms of computersoftware and hardware. The techniques described may constitutemachine-executable instructions embodied within a tangible ornon-transitory machine (e.g., computer) readable storage medium, thatwhen executed by a machine will cause the machine to perform theoperations described. Additionally, the processes may be embodied withinhardware, such as an application specific integrated circuit (“ASIC”) orotherwise.

A tangible non-transitory machine-readable storage medium includes anymechanism that provides (i.e., stores) information in a form accessibleby a machine (e.g., a computer, network device, personal digitalassistant, manufacturing tool, any device with a set of one or moreprocessors, etc.). For example, a machine-readable storage mediumincludes recordable/non-recordable media (e.g., read only memory (ROM),random access memory (RAM), magnetic disk storage media, optical storagemedia, flash memory devices, etc.).

The above description of illustrated implementations of the invention,including what is described in the Abstract, is not intended to beexhaustive or to limit the invention to the precise forms disclosed.While specific implementations of, and examples for, the invention aredescribed herein for illustrative purposes, various modifications arepossible within the scope of the invention, as those skilled in therelevant art will recognize.

These modifications can be made to the invention in light of the abovedetailed description. The terms used in the following claims should notbe construed to limit the invention to the specific implementationsdisclosed in the specification. Rather, the scope of the invention is tobe determined entirely by the following claims, which are to beconstrued in accordance with established doctrines of claiminterpretation.

1. A light detection and ranging (LIDAR) sensor system for a vehicle,the LIDAR sensor system comprising: one or more LIDAR pixels, wherein atleast one of the one or more LIDAR pixels includes: a dual-polarizationoptical antenna configured to: (i) emit a transmit beam having a firstpolarization orientation, and (ii) detect a return beam having a secondpolarization orientation; a second optical antenna offset from thedual-polarization optical antenna by a particular distance, wherein thesecond optical antenna is configured to detect the return beam havingthe second polarization orientation; and one or more receiversconfigured to generate one or more signals in response to detecting thesecond polarization orientation of the return beam.
 2. The LIDAR sensorsystem of claim 1, wherein the dual-polarization optical antennaincludes a two-dimensional (2D) polarization splitting grating couplerhaving a first port and a second port, wherein the 2D polarizationsplitting grating is configured to receive a transmit signal on thefirst port and is configured to provide the return beam having thesecond polarization orientation to the second port coupled to at leastone receiver of the one or more receivers.
 3. The LIDAR sensor system ofclaim 1, wherein the second optical antenna comprises asingle-polarization optical antenna coupled to the one or more receiversto provide the second polarization orientation of the return beam to theone or more receivers.
 4. The LIDAR sensor system of claim 3, whereinthe single-polarization optical antenna includes a one-dimensional (1D)polarization grating coupler.
 5. The LIDAR sensor system of claim 1,wherein the first polarization orientation is orthogonal to the secondpolarization orientation.
 6. The LIDAR sensor system of claim 1, whereinthe one or more receivers comprise: a first receiver configured togenerate a first electrical signal in response to the dual-polarizationoptical antenna and in response to a first local oscillator signal; anda second receiver configured to generate a second electrical signal inresponse to the second optical antenna and in response to a second localoscillator signal.
 7. The LIDAR sensor system of claim 6, wherein thefirst local oscillator signal is polarized with a third polarizationorientation and the second local oscillator signal is polarized with thethird polarization orientation.
 8. The LIDAR sensor system of claim 7,wherein the dual-polarization optical antenna is configured to couplethe return beam into the at least one of the one or more LIDAR pixels asa return signal, wherein the return signal is polarized with the thirdpolarization orientation.
 9. The LIDAR sensor system of claim 8, whereinthe third polarization orientation is the first polarization orientationor the second polarization orientation.
 10. The LIDAR sensor system ofclaim 6, wherein the first receiver includes a first optical mixer andthe second receiver includes a second optical mixer, wherein the firstreceiver includes a first diode pair coupled to the first optical mixerand configured to provide the first electrical signal, wherein thesecond receiver includes a second diode pair coupled to the secondoptical mixer and configured to provide the second electrical signal.11. The LIDAR sensor system of claim 1, wherein the transmit beam andthe return beam have a narrow-band near-infrared wavelength.
 12. TheLIDAR sensor system of claim 1, wherein the particular distance isconfigured to compensate for a beam walk-off of the return beam.
 13. Anautonomous vehicle control system for an autonomous vehicle, theautonomous vehicle control system comprising: a light detection andranging (LIDAR) device including one or more LIDAR pixels, wherein atleast one of the one or more LIDAR pixels includes: a dual-polarizationoptical antenna configured to: (i) emit a transmit beam with a firstpolarization orientation, and (ii) detect a return beam having a secondpolarization orientation; a second optical antenna offset from thedual-polarization optical antenna by a particular distance, wherein thesecond optical antenna is configured to detect the return beam havingthe second polarization orientation; and one or more receiversconfigured to generate one or more signals in response to detecting thesecond polarization orientation of the return beam; and one or moreprocessors configured to control the autonomous vehicle in response tothe one or more signals.
 14. The autonomous vehicle control system ofclaim 13, wherein the dual-polarization optical antenna includes atwo-dimensional (2D) polarization splitting grating coupler having afirst port and a second port, wherein the 2D polarization splittinggrating is configured to receive a transmit signal on the first port andis configured to provide the return beam having the second polarizationorientation to the second port coupled to at least one receiver of theone or more receivers.
 15. The autonomous vehicle control system ofclaim 13, wherein the second optical antenna comprises asingle-polarization optical antenna that includes a one-dimensional (1D)polarization grating coupler.
 16. The autonomous vehicle control systemof claim 13, wherein the particular distance is configured to compensatefor a beam walk-off of the return beam.
 17. The autonomous vehiclecontrol system of claim 13 further comprising: a rotating mirrorconfigured to direct the transmit beam into a LIDAR environment andconfigured to direct the return beam onto the at least one of the one ormore LIDAR pixels; and a birefringent slab positioned between therotating mirror and the at least one of the one or more LIDAR pixels,wherein the birefringent slab is configured to direct the return beamhaving the second polarization orientation onto the dual-polarizationoptical antenna or the second optical antenna based on a time differencein a rotation of the rotating mirror.
 18. An autonomous vehiclecomprising: a light detection and ranging (LIDAR) device including oneor more LIDAR pixels, wherein at least one of the one or more LIDARpixels includes: a dual-polarization optical antenna configured to: (i)emit a transmit beam with a first polarization orientation, and (ii)detect a return beam having a second polarization orientation; a secondoptical antenna offset from the dual-polarization optical antenna by aparticular distance, wherein the second optical antenna is configured todetect the return beam having the second polarization orientation; andone or more receivers configured to generate one or more signals inresponse to detecting the second polarization orientation of the returnbeam; and one or more processors configured to control the autonomousvehicle in response to the one or more signals.
 19. The autonomousvehicle of claim 18, wherein the second optical antenna comprises asingle-polarization optical antenna that includes a one-dimensional (1D)polarization grating coupler.
 20. The autonomous vehicle of claim 18,wherein the particular distance is configured to compensate for a beamwalk-off of the return beam.